Cloud computing and edge AI are two rapidly expanding technologies that are revolutionizing IT. By 2026, the cloud computing market alone is forecast to be worth $947.3 billion, according to Spacelift, an infrastructure development company.¹ The market for edge AI has boomed over the last decade, with news outlet TMCnet projecting that the edge AI hardware market will be worth $58.9 billion by 2030.² Cloud computing and edge AI are on their way to becoming indispensable parts of the technology sector, and cybersecurity experts need to know how to protect them. Discover the impact of these technologies and learn how cybersecurity professionals are critical to their functioning.

What is Cloud Computing?

Before cloud computing, users could only access the Internet and its resources from local networks, which are groups of interconnected machines that share Internet access and resources. With the development of cloud computing in the nineties and 2000s, users gained access to Internet services on-demand from any location. Today, cloud computing is a huge part of daily life at home, at work, and everywhere in between.

The “Big Three” cloud computing companies encountered in daily life are Amazon Web Services, Microsoft Azure, and Google Cloud, according to Cloudwards software security company, and each provides a bevy of cloud applications and services.³ One example is Google Maps, which collects traffic data through satellite imagery, street views, and user-generated GPS routes. Combined with AI learning algorithms and data from third party resources, Google Maps Product Director Ethan Russell states that the platform is “updated constantly–literally, every second of every day.”⁴ Because Google Maps exists on a cloud server, users can access an updated version of the application on-demand from wherever they are.

Another advantage of cloud computing is that companies can choose from several types of cloud computing depending on their needs. Four types of clouds are available for companies, according to Microsoft: public clouds, private clouds, hybrid clouds, and multiclouds.⁵ Public clouds are available for any user, while private clouds are available only to a specific company, business, or organization. A hybrid cloud gives companies the benefit of both types of clouds—public functions are available to all users while some tasks can remain private if they contain proprietary or sensitive information. A multicloud company uses more than one cloud—this kind of use is mostly seen in large-scale companies. With so many options, cloud computing can be tailored to each organization’s needs.

The drawback of cloud computing is that it relies on a stable Internet connection. Without a connection, cloud services are unavailable. Consider the navigation app AllTrails. With a subscription to the service, hikers can navigate trails live, see the location of landmarks in the area, plan for downed trees and flooded creeks, and receive notifications when veering off-trail. However, without a network connection, these services are unavailable. If a hiker doesn’t have a map and is unfamiliar with the trail, they can quickly end up in a dangerous situation. AllTrails has tried to circumvent this issue by offering additional offline access for premium subscriptions, but downloading offline maps still requires an Internet connection.⁶

What is Edge AI?

AI edge computing does not involve the cloud in its capabilities. Data can be retrieved from the cloud, but it is stored on the edge of computer networks and on smart devices, closer to where it is generated. Edge AI applications can be programmed on many devices, such as cameras, sensors, monitors, smartphones, laptops, cars, appliances, and more. These devices can capture, analyze, and act on data without the data having to be sent elsewhere to process.

One of the primary benefits of edge AI is speed. Because it delivers data processing, analysis, and storage close to physical endpoints, edge AI can enable almost real-time responsiveness. A common example is home security systems that work on edge AI. As soon as an anomaly occurs or an intruder is detected, the system notifies the user first instead of sending data to a central processing server. These seconds are invaluable in emergency situations. Another example is self-driving cars, where AI must make quick decisions about traffic maneuvers and predict the behavior of other drivers. Yet another example of edge AI is Novetta by Amazon Web Services. Novetta employs edge AI to monitor sensors and cameras in disaster areas, keep track of first responders, and determine the location of critical equipment.⁷

Another benefit of AI edge computing is security. Data from edge AI doesn’t have to travel to another location to be processed, which lessens opportunities for cyber attackers to intercept it. However, cybersecurity for edge AI is still crucial to prevent local threats such as unauthorized users, data corruption, and viruses.

Yet another advantage of edge AI is that it can process data and act upon it independently, which doesn’t require an Internet connection. This is because AI can be trained with machine learning and deep learning algorithms. These algorithms, operating offline, help users make decisions based on what AI has learned from past experiences, according to the Edge Impulse development platform.⁸

Medical devices are a leading-edge example of edge AI’s independence from an Internet connection. Heart monitors, portable x rays, and scanners can be programmed with machine learning and then taken offline to function on edge AI. Consider the benefits of offline healthcare technology to areas where access to healthcare is remote or may not be available. In these cases, edge AI applications can lead to more accurate diagnoses and better health outcomes.

What Role Does Cloud Computing Have With Edge AI?

Cloud computing’s role in edge AI is to help AI run more efficiently. Data from edge AI still needs to be transmitted to the cloud when available, which helps make updates to edge AI applications and collect data from additional sources. Spotify is a good example of this procedure. The app enables users to listen to songs and audiobooks that are stored on Google Cloud. If the right plan is selected, users can download files for offline access. Every thirty days, though, users must log in to the cloud again to verify their subscription is up to date, perform security updates, and ensure data is sent to third parties who have an interest in users’ listening data.⁹

The cloud also helps train edge AI because it provides AI with millions of pieces of data that AI uses to uncover patterns, predict how data will evolve, and increase efficiency, according to IT company Infiniticube.¹⁰ Cloud computing models are therefore essential to AI’s functions because edge AI makes decisions using the latest cloud-based information. Infiniticube refers to this as “cloud for training, edge for execution,” showing how the two technologies are critical to supporting one another.¹⁰

Both cloud computing and edge AI rely on cybersecurity experts to protect sensitive data, ensure applications run smoothly, and prevent cyberattacks. This is especially true when more than one type of cloud is being used, and when multiple users are accessing the cloud. Edge AI hardware and software must also be secure, even when they’re not connected to a network, so hardware and software security is key.

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Sources

1. Spacelift. “55 Cloud Computing Statistics for 2025.” July 8, 2025. Retrieved July 14, 2025, from https://spacelift.io/blog/cloud-computing-statistics#top-cloud-computing-statistics.
2. TMCnet. “Edge AI Hardware Market worth $58.90 billion by 2030 – Exclusive Report by MarketsandMarkets™.” July 4, 2025. Retrieved July 14, 2025, from https://www.tmcnet.com/usubmit/2025/07/04/10219225.htm.
3. Cloudwards. “Top Cloud Computing Examples Based on Service Types and Models in 2025.” June 13, 2025. Retrieved July 14, 2025, from https://www.cloudwards.net/cloud-computing-examples/.
4. Google Maps Platform. “9 things to know about Google’s maps data: Beyond the Map.” September 30, 2019. Retrieved July 14, 2025, from https://mapsplatform.google.com/resources/blog/9-things-know-about-googles-maps-data-beyond-map/.
5. Microsoft Security. “What is cloud security?” Retrieved July 14, 2025, from https://www.microsoft.com/en-us/security/business/security-101/what-is-cloud-security?msockid=36225eb5a61660553b5a4b9ca21666fc.
6. AllTrails. “Summer Update 25.” Retrieved July 14, 2025, from https://www.alltrails.com/update/2025-summer.
7. AWS Events. “Data Migration and Edge Computing with the AWS Snow Family (STG214) – Novetta.” February 20, 2020. Retrieved August 22, 2025, from https://www.youtube.com/watch?v=0gfkyrAUDS4.
8. Edge Impulse. “What is edge machine learning (edge ML)?” June 19, 2025. Retrieved July 14, 2025, from https://docs.edgeimpulse.com/knowledge/concepts/what-is-edge-machine-learning.
9. Spotify. ”Listen Offline.” Retrieved July 14, 2025, from https://support.spotify.com/us/article/listen-offline/.
10. Infiniticube. “What Role Does Cloud Computing Play in Edge AI?” October 16, 2024. Retrieved July 14, 2025, from https://infiniticube.com/blog/what-role-does-cloud-computing-play-in-edge-ai/.